Research

I focus on integrating, into robots, as much formally represented
domain knowledge as possible
especially for realtime algorithms and other
software close to the hardware, the controller(s) and the sensor(s).
In other words, I am on a continuous quest for the
holy grail of the (mythical)
“robotics
ontology”…

This puts my research in the (currently sparsely populated) corner of Artificial Intelligence that is opposite to the (currently extremely popular) (deep) learning. My knowledge representations do include the relations with which the latter techniques can be integrated into any robotic system, in a systematic way. (Like any other AI technique for that matter.) That integration consists of how to configure the many “magic numbers” that the (so-called) “model-less” techniques require for a proper working in a specific task and application context; this configuration in itself requires quite some understanding of the intriciate dependencies between the perception, plans, control and monitoring activities in a robotic system.

My research takes place in close cooperation with
Erwin Aertbeliën (super expert in dissecting and programming the most difficult robot tasks and in numerical solvers),
Wilm Decré (my main liason with industrial projects),
Joris De Schutter (former supervisor, co-creator of most of my “robot skills” R&D, reads robotics challenges as no-one else),
Goele Pipeleers (for solvers of constrained optimization problems),
Jan Swevers (main liason for all things control),
René van de Molengraft (core co-creator of my approach towards system-of-systems architectures, and especially to “lazy” robot skills),
Eric Demeester (main liason for shared control and industrial robot vision),
Peter Slaets (main liason for unmanned (“autonomous”) shipping),
Mark Versteyhe (main liason to the mechatronics industry in Flanders),
and a manageably small set of
PhD students and
postdocs. All of the KU Leuven people have enjoyed the view from standing on the shoulders of our robotics founding father Rik van Brussel.

Research question 1

How can knowledge-driven
(“affordance-based”)
robot programming, perception and learning be made more
realtime, while still taking into account more
prior knowledge about the tasks, the robots, the objects they interact with, and the environment they have to survive in?

Summary of results:
the information and software architectures for the motion stack
and the perception stack of robotics systems-of-systems are
extremely similar, composable and formally verifiable. The
“knowledge” is represented as constraints between
parameters in the Bayesian model. The traditional Bayesian model is
extended to be hierarchical, in the sense that it must be possible
to let different sets of knowledge constraints apply to different parts of
the Bayesian model; this is a pragmatic way to introduce the all-important
concept of “context”.

Research driver 1

Instead of chasing one of the many non-constructive “definitions” of levels of autonomy (like “Sheridan's 10”, Parasuraman, Sheridan & Wickens, IEEE Trans. Systems, Man, Cybernetics, 2000) we should design robots that can pass the “Trustworthy Turing Test” (TTT). That means that they are always able to answer the following questions, in increasing order of decision making quality/complexity and of what if? answerability:

Level

Description

One system — One task

1

What am I doing?

2

Why am I doing it?

3

How am I doing it,…

4

…and how well am I doing it…

4b

…and how do I decide to stop doing it?

One system — Multiple tasks

5

What could I be doing instead,…

5b

…and still be useful,…

5c

…and how do I decide to switch what I am doing?

6

What is threatening my progress,…

6b

…and how can I make myself resilient,…

6c

…and how do I decide to add a particular resilience?

Multiple systems — Multiple tasks

7

What progress of others am I threatening,…

7b

…and how can I make myself behave better,…

7c

…and how do I decide to adapt a particular better behaviour?

8

What other machines and humans can I cooperate with,…

8a

…and how do I find out how can we coordinate our cooperation,…

8b

…and how do we decide, together, what coordination to adopt,…

8c

…and how do we monitor our coordination,…

8d

…and how do we decide that someone has cooperation problems?,…

The answers to these questions help human observers to assess whether the system is “aware” of the context, purpose and consequences of its actions, and the motivations behind its decisions.

The last time I looked, the state of the art in robotics was still at level 0…

Research driver 2

The societal expectation to have trustworthy Artificial Intelligence

These TTTs are tough to realise because it requires thorough scientific methods, but it is my hypothesis that they are the only way to build “AI” technology that is refutable/falsifiable, respects causality, and is predictable to the extend of being certifiable.
In other words, robotic system developers can only claim to be working ethicallyif and only if they strive for full TTTs in all their systems.

Simplerefers to the effort to understand.
Easy refers to the effort to implement.
Two concepts derived from ``simple'' are worth introducing too:
simplicity refers to the (positive) ambition to remove everything except what matters;
simplistic refers to the (negative) outcome where so much has been removed that what remains is useless,
or even dangerous.
Unfortunately, many newcomers to a domain start using the solutions that are popular,
without realising that they are popular because they are simplistic,
as a result of letting “easy” take precedence over “simplicity”.
In politics, this behaviour has gotten the well-deserved name of
populism.

Explanations exist; they have existed for all time; there is always a well-known solution to every human problem — neat, plausible, and wrong.
— Henry Louis Mencken

“Sense-Plan-Act” and “Subsumption Architectures”
are things of the past in robotics, to be
replaced by the “Every robot task is a constraint-optimization
problem”
paradigm, that links continuous, discrete and symbolic
knowledge, at runtime, and all the time.

Take all criticism seriously but not personally. If there is truth or merit in the criticism, try to learn from it. Otherwise, let it roll right off you.

A wealth of fundamental problems lie waiting for scientific solutions in
daily industrial practice, for anyone who takes the effort to discover
them.

Learn to love throwing away years of research and development: real
progress should not be hindered by deprecated
legacy. Irrespective of how much effort it
took to create that legacy, there is no better feeling for a scientist than to replace it by
improved insights.

Research question 2

What are the formal
Domain Specific
Languages (DSLs) that can make the knowledge representation (and hence the programming of robots) a
lot more easy? And, at the same time, a lot more
semantically consistent, and (hence!) deterministic,
and (hence?) explainable,
and (hence?) verifiable, and (hence!) certifiable, and (hence?) societally trustworthy.

Preliminary answer: by creating lots of small ontologies, with their Primitives, Relationships, Constraints and Tolerances encoded in
languages such as JSON-LD, that support
N-ary relationships and
context-specific hierarchical composition as first-class citizens.

Summary of results:
I was a key creator of the BRICS Component Model, and of its successor the
System Composition Pattern,
which is a scientific paradigm to support the design, development,
deployment and runtime adaptation of complex robotics and other
cyber-physical)
systems.

Research question 3

Which new design paradigm can provide cheap, light and
safe (hence, “lousy”) robot hardware? This is a
necessary evolution before robotics platforms can become a
commodity.

Preliminary answer: confidential, for now.

The robotics community seems not to be interested in realising this
ambition of developing highly trustworthy robots. Hence, it prepares itself for a
Robotics Winter:
society will (should!) not accept automatic decision making by machines without the
latter
being able to provide full explanations of their deeds and their intentions.

Science is never value-free, if we take into account the choices we make what (not) to research!

Robots can never be science-free, if we want them to be predictable and certifiable!

Research question 4

What is the essential and minimal structure to model the software aspects of robotic systems?
How should robot control software be developed in the future?
What architectural patterns can help us cope with the exploding complexity in knowledge,
task variations, and distribution over several sub-systems?

Preliminary answers: (i) by systematically applying a small set of system-of-systems composition patterns, (ii) by clean separation of the information, software and hardware architectures, and (iii) by generating the robots' motions more and more by preview and precognitive control.

Preview control is the “information architectural” model behind
Model-predictive Control
(MPC) (and its estimation dual
Moving Horizon Estimation); it
adds a symbolic/modelling part to the numerical robot state, to represent the task-level aspects of intentions, progress and benefits of an ongoing robot action, to allow making decisions about altering that control on the basis of what the future is expected to bring. This information could be obtained as a side-effect of the control-level optimizations done in an MPC, by
solvingConstrained Optimization Problem
using finite horizons over time and state space. The MPC state in itself can already be
“hybrid”, in that it
contains discrete as well as continuous parts; the symbolic part is involved in a
“Constraint Satisfaction Problem” which is solved by
reasoning systems
and extends the MPC with a
closed world
of knowledge relationships (which is the symbolic equivalent of a “finite horizon”).

When the robot itself is able to fill in the symbolic information in the preview control model, we call this control mode pre-cognitive control. We're not there yet…

Autonomism_ and
separatism are outdated concepts in the European Union: the political leaders of the member state nations tend not to tell their citizens that most of their influence has already been transferred, legally or de facto, to the European level, or, worse, to global companies.

As a citizen of Leuven, Belgium, I am governed by, and pay taxes to, five levels of government: town (scale: 100.000 citizens), province (scale: 1M), region (scale: 5M), country (scale: 10M), EU (scale: 500M). Having that many levels has become highly ineffective, since the world has shrunk its physical and informational distances with two orders of magnitude since the creation of these nation states. So, just three levels would make a lot more sense to me.

I would love to be able to be a professor in the “University of the Low Countries”, instead of having my teaching research and societal services being restricted to just one university. Why do parents accept that their children loose access to more than 80% of all Dutch language professors, as soon as they register to a university in Flanders or the Netherlands, while they pay taxes to finance all of the dozens and dozens of the institutes that employ these professors…?

Research question 5

What is the essential and minimal structure to model the functional aspects of robotic systems, such that

all entities, relations, and constraints are given a unique and semantically unambiguous place.

no model must ever be changed when composed into a larger system, except for some configuration of parameters in the model.

all physical constraints can be covered: energy sources, power transformation to the mechanical domain, mechanical transmmissions, joints, kinematic chains.

all artificial constraints can be covered: tasks for individual robots as well as (cooperative) systems of robots.

Best-practice answer, after three decades of practicing, and just for the functional aspects:

The following questions can not really be called “research questions”, because the answers are obvious. But, the last time I looked, these answers are not accessible in state of the art publications, and not at all in educational curricula. So, I publish the questions here, and leave the answers as a warming-up exercise to the reader.

Why don't highly-educated decision makers (yes rectors, CEOs and ministers, it's you I'm referring to…) understand that an ICT platform that is only accessible with a login creates huge ICT monopolies like Apple (AppStore/iTunes), Google (Play), Facebook, Twitter or LinkedIn?
Aren't these the same people who do understand (I think…) why it does not make sense to let one login into the telephone system, the internet, or the World Wide Web.

Why do universities or government organisations put clickable logo's of the above-mentioned companies on all their websites, and hence introduce discrimination and stimulate inequality?

Why don't highly-educated decision makers understand the
fallacies of the free market, and hence fail to create ICT regulation and guidelines that lead to free market ICT platform with fair entrance and competition conditions? What is so difficult about the golden rule that a provider of a platform (ICT and others) should never be allowed to become a provider of services on top of that platform? And why should decision makers never allow platform providers to put a password on the platform to access the data that actually are owned by the user?

Why don't they understand that all the investments they make to close the digital divide only makes it larger? For example, do they really believe that providing money to schools to use Microsoft Word/Excel, Apple FaceTime or the MathWorks Matlab helps the pupils to become empowered IT users in their later life? Maybe they don't realise that the moment these students leave school and start their career, their employers have to cough up several thousands of euros to let them continue with the same ICT habits?

Most educational systems worldwide are government-funded training centres for Microsoft Office, which is a major showstopper for the ICT empowerment of our society.
Real ICT empowerment, and long-term societal benefits, can be reached by teaching our kids how to use text editor (like Vim) and use them to create all of their documents with standard HTML5. Drawings should be made with tools using the open standard SVG; Inkscape is one of such tools, available for almost all computer platforms.
Similar remarks hold about replacing training with Skype by training with
WebRTC-based alternatives.

Bibliometrics-driven
science policies have created a schism between scientists and society, hindering
the impact and application of scientifc research, and the creation of
new paradigms and added-value innovation.
This schism is painfully visible by the lack of a decent answer to valid questions like “In which documents can I find the
state-of-the-art in robotics?”

The best publication a modern PhD student can produce is one that explains which dozens of existing “state of the art” publications are all just other ways of expressing (and naming…) the same scientific models.

Continuous education to individuals, organisations and companies

I consider an academic degree as a more than decent starting point for a professional career, but nothing more. Hence, I offer state of the art update classes in all areas of my expertise, at consultancy fees.
Individuals, organisations (press, governmental administations,…) and companies can apply, starting from half a day to three day courses.

The fees go for 100&percnt; to KU Leuven or TU Eindhoven funds to support my research. Both universities have selected continuous education as one of its major missions, but have not yet been able to provide much in terms of concrete contents; so, mine is a humble contribution to that mission.

Lessons learned from past projects:
BRICS
(Best Practice in Robotics, 2009–2013) and
Rosetta (Robot control
for skilled execution of tasks in natural interaction with humans; based on
autonomy, cumulative knowledge and learning, 2009–2013) have
helped me understand what step changes are required in
the domains of, respectively, systems software engineering and task
specification.
In Pick-n-Pack (2012–2016), the insights gained in the above-mentioned projects were turned into innovative software solutions, in the context of “robotics” food production lines.
RoboHow (2012–2016) complemented the above-mentioned ones by (preliminary versions of) formal representations of the
knowledge of robot motions and tasks.
Sherpa (2013–2017) and the
ongoing H2020 projects allow the positively brutal confrontation of our
insights with the real world of various challenging application domains,
and with the strong but highly justified requirements from end-users and
industrial integrators.

I have been very active in promoting the introduction into the robotics
domain of the separation of concerns concept, originally
via the 4Cs (of Radestock and Eisenbach, 1996, see below),
which I refined into the 5Cs:
Computation, Communication, Coordination,
Composition, and Configuration.

The first “real” publication about the 5Cs was this
White
Paper, created in the context of the
Robot Standards (RoSta)
project: Erwin Prassler, Herman Bruyninckx, Klas Nilsson, and Azamat
Shakhimardanov,
The Use of Reuse for Designing and Manufacturing Robots.
Klas deserves
the credit of introducing me to the seminal
paper by Matthias Radestock and Susan Eisenbach,
Coordination in evolving systems, Trends in Distributed Systems.
CORBA and Beyond, Springer-Verlag, 1996, pp. 162-176.

The contributions to the education of our young
engineers that I value most are my emphasis on (i) system-level thinking, and
(ii) attitude of constructively critical evaluation of all
available sources of information, starting with
pseudo-peer reviewed
open content such as the Wikipedia.
Our students typically score poorly on both aspects, which I think are fundamental for
Europe's ability to maintain an innovative R&D ecosystem. The future
does not belong to those who posess the most knowledge,
but to those who are able to understand how and where
to apply that knowledge.

My most “revolutionary” contribution to education is to use
professional mailing
lists as first-class teaching tool: this is the most effective (albeit labour
intensive and not always efficient…) approach to provide
learning feedback to students on an individual basis,
answering to their problems when they are ready for it. This best
practice comes directly from my long-term, intensive immersion in, and
contributions to, the “open source” community.

Universities recently started to promote asocial media technologies
as revolutionary additions to traditional educational practice. I'm sorry, but
that technology existed (and has been used, by myself and many others) already
a long time before companies like Facebook, Twitter and
Balckboard made that technology proprietary and put it behind a
passwords.

If universities are serious about
lifelong learning,
they stimulate their professors, staff and students to develop educational contents primarily within the
Wikipedia
ecosystem: Wiki articles, Wiki books, and Wiki courses. The others pay lots of money to keep their educational material behind passwords, preventing their students to access the material almost immediately after they have passed a course…

Society should no longer consider universities as the fundamental units to
organise, evaluate and promote science and education, but on the academic system of students, researchers and professors. Indeed, rankings of universities are meaning- and useless, since quality is determined by the academic individuals and their (international) networks, not by the legal entities that should just be responsible for the logistics.

In any government-sponsored academic system, students should get the opportunity to study with all professors paid by the system, irrespective of the university those professors “belong to”. Currently, students are cut off from most of their educational opportunities as soon as they (have to) register at one particular university.

(Robotics) PhD students of all countries, unite! Not to write yet another
thousand papers “full” of Least
Publishable Units of knowledge, but to let your progress have an impact
on solving the real societal challenges of this century

Progress comes from fierce and ruthless confrontation of ideas, not of people

PhD texts often have large literature surveys, that add no value beyond just listing key-value pairs of a publication connected to a short string summarizing its contributions. But as an evaluator, I am intersted in such list, but in the insights about why the publication is added, and how it improved the PhD student's research.

Wilm Decré,
PhD (co-supervised with Joris De Schutter)
on Optimization-Based Robot Programming with Application to Human-Robot
Interaction , 2011.
Prior to joining our group again, Wilm was CTO of the company he co-founded, SoundTalks.

Tinne De Laet,
PhD on Rigorously Bayesian Multitarget Tracking and Localization, defended on May 25, 2010.
She is now Professor at the Faculty of Engineering Science, University of Leuven, responsible
for student tutorial services.

The most important thing I can offer to potential post
docs is a lot of opportunities to get immersed into the most
vibrant core of the Dutch-Flemish robotics research scene, academic as well as industrial, including lots of
interactions with dozens of robotics groups in Europe.

I am a firm believer in the maturity and responsibility of master and PhD students.
Hence, I do not want to be their “supervisor” but rather their
“somewhat more experienced coach”. In return, I expect them always to have a clear idea
about where exactly they want to go with their research. My rule
of thumb for a PhD student is to have 2–3 research
hypotheses written out in full, at all times. They need them, not only to explain to visitors what their research is all about, but also to
keep their strength and self-confidence, since I flood them continuously
with (only potentially) good ideas, papers and software, with
constructive criticism, and with stimuli to “think weird” and “design big”. I do
realise that such a turmoil of scientific discussions and doubts can take
some time to adapt to, and requires strong nerves to keep one's research
focus. However, I do not apologize for this behaviour of mine.

Student internships and master theses

I welcome Master students from universities all over Europe, and
I'm especially interested in computer-literate students (Linux, C, Lua, HTML5, and, to a lesser
extent, “everything and the kitchen sink” wrong-level languages such C++
or Java). I will stimulate them to contribute to
Free and Open Source
Software projects, to make the latter better suited for robotics.

ICT empowerment is
about much more than just using a computer for what you did 20 years ago
already with pen, paper and file cabinets. It's all about standing on the
shoulders of thousands and thousands of open source midgets, and,
especially, about throwing out that Outlook programme of yours, because it
only supports
top posting, sigh…

The best thing HR managers can do with the administrative collaborators in their organisation
is to force them to learn how to use real databases, and web applications. It will not be easy,
but quickly they will not want to return anymore to the old days when information was shared by
sending around Word documents or Excel files, and then trying to keep that information updated,
consistent, and reusable in other contexts.

It can take ten years to understand how something really works, but only ten days to teach it
to students. However, teaching it to students of all backgrounds will take ten years
again.

Logical consequence of the insight above: be very careful with professors who claim they can (let their students) write one decent publication a year, or one excellent one every three years.

We should not expect PhD students to advance the state of the art, but be very happy if they could first, understand it, and then reduce it: nothing is indeed advancing our insights more than the introduction of a new level of abstraction that puts previously seemingly unrelated things into a new context that makes a lot more sense.

I do not have a Skype account, nor do I take part in asocial media.
I am not planning to get those accounts,
because of pragmatic and ethical principles:
these initiatives introduce proprietary protocols and/or prevent bias-free,
inter-community, multi-vendor communication.
The inevitable result is
to
create monopolies, and hence prevent fair markets of
VOIP or social
networking as emerging communication instruments.
It's only 40
years ago that our society succeeded to escape from the traditional
telecom monopolies,
but it seems not to have learned anything from those experiences…

If you are prepared to invest in fairness and freedom, I suggest to use the
facilities offered by the free market of teleconferencing via the
traditional telephone line and to use open VOIP protocols. Or, preferably, use
Open Standards formats, such as
WebRTC, and
user-friendly implementations of it such as
JitsiMeet'.